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Forensic Analytics Methods and Techniques for Forensic Accounting Investigations

ISBN-10: 0470890460
ISBN-13: 9780470890462
Edition: 2011
Authors: Mark Nigrini
List price: $100.00 Buy it from $69.65
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Description: The book will review and discuss (with Access and Excel examples) the methods and techniques that investigators can use to uncover anomalies in corporate and public sector data. These anomalies would include errors, biases, duplicates, number  More...

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Book details

List price: $100.00
Copyright year: 2011
Publisher: John Wiley & Sons, Incorporated
Publication date: 6/7/2011
Binding: Hardcover
Pages: 480
Size: 7.50" wide x 10.50" long x 1.50" tall
Weight: 2.486
Language: English

The book will review and discuss (with Access and Excel examples) the methods and techniques that investigators can use to uncover anomalies in corporate and public sector data. These anomalies would include errors, biases, duplicates, number rounding, and omissions. The focus will be the detection of fraud, intentional errors, and unintentional errors using data analytics. Despite the quantitative and computing bias, the book will still be interesting to read with interesting vignettes and illustrations. Most chapters will be understandable by accountants and auditors that usually are lacking in the rigors of mathematics and statistics. The data interrogation methods are based on (a) known statistical techniques, and (b) the author's own published research in the field.

Preface xi
About the Author xv
Using Access in Forensic Investigations
An Introduction to Access
The Architecture of Access
A Review of Access Tables
Importing Data into Access
A Review of Access Queries
Converting Excel Data into a Usable Access Format
Using the Access Documenter
Database Limit of 2 GB
Miscellaneous Access Notes
Summary
Using Excel in Forensic Investigations
Pitfalls in Using Excel
Importing Data into Excel
Reporting Forensic Analytics Results
Protecting Excel Spreadsheets
Using Excel Results in Word Files
Excel Warnings and Indicators
Summary
Using PowerPoint in Forensic Presentations
Overview of Forensic Presentations
An Overview of PowerPoint
Planning the Presentation
Color Schemes for Forensic Presentations
Problems with Forensic Reports
Summary
High-Level Data Overview Tests
The Data Profile
The Data Histogram
The Periodic Graph
Preparing the Data Profile Using Access
Preparing the Data Profile Using Excel
Calculating the Inputs for the Periodic Graph in Access
Preparing a Histogram in Access Using an Interval Table
Summary
Benford's Law: The Basics
An Overview of Benford's Law
From Theory to Application in
Years
Which Data Sets Should Conform to Benford's Law?
The Effect of Data Set Size
The Basic Digit Tests
Running the First-Two Digits Test in Access
Summary
Benford's Law: Assessing Conformity
One Digit at a Time: The Z-Statistic
The Chi-Square and Kolmogorov-Smirnoff Tests
The Mean Absolute Deviation (MAD) Test
Tests Based on the Logarithmic Basis of Benford's Law
Creating a Perfect Synthetic Benford Set
The Mantissa Arc Test
Summary
Benford's Law: The Second-Order and Summation Tests
A Description of the Second-Order Test
The Summation Test
Summary
Benford's Law: The Number Duplication and Last-Two Digits Tests
The Number Duplication Test
Running the Number Duplication Test in Access
Running the Number Duplication Test in Excel
The Last-Two Digits Test
Summary
Testing the Internal Diagnostics of Current Period and Prior Period Data
A Review of Descriptive Statistics
An Analysis of Alumni Gifts
An Analysis of Fraudulent Data
Summary and Discussion
Identifying Fraud Using the Largest Subsets and Largest Growth Tests
Findings From the Largest Subsets Test
Running the Largest Subsets Test in Access
Running the Largest Growth Test in Access
Running the Largest Subsets Test in Excel
Running the Largest Growth Test in Excel
Summary
Identifying Anomalies Using the Relative Size Factor Test
Relative Size Factor Test Findings
Running the RSF Test
Running the Relative Size Factor Test in Access
Running the Relative Size Factor Test in Excel
Summary
Identifying Fraud Using Abnormal Duplications within Subsets
The Same-Same-Same Test
The Same-Same-Different Test
The Subset Number Duplication Test
Running the Same-Same-Same Test in Access
Running the Same-Same-Different Test in Access
Running the Subset Number Duplication Test in Access
Running the Same-Same-Same Test in Excel
Running the Same-Same-Different Test in Excel
Running the Subset Number Duplication Test in Excel
Summary
Identifying Fraud Using Correlation
The Concept of Correlation
Correlation Calculations
Using Correlation to Detect Fraudulent Sales Numbers
Using Correlation to Detect Electricity Theft
Using Correlation to Detect Irregularities in Election Results
Detecting Irregularities in Pollution Statistics
Calculating Correlations in Access
Calculating the Correlations in Excel
Summary
Identifying Fraud Using Time-Series Analysis
Time-Series Methods
An Application Using Heating Oil Sales
An Application Using Stock Market Data
An Application Using Construction Data
An Analysis of Streamflow Data
Running Time-Series Analysis in Excel
Calculating the Seasonal Factors
Running a Linear Regression
Fitting a Curve to the Historical Data
Calculating the Forecasts
Summary
Fraud Risk Assessments of Forensic Units
The Risk Scoring Method
The Forensic Analytics Environment
A Description of the Risk-Scoring System
P1: High Food and Supplies Costs
P2: Very High Food and Supplies Costs
P3: Declining Sales
P4: Increase in Food Costs
P5: Irregular Seasonal Pattern for Sales
P6: Round Numbers Reported as Sales Numbers
P7: Repeating Numbers Reported as Sales Numbers
P8: Inspection Rankings
P9: High Receivable Balance
P10: Use of Automated Reporting Procedures
Final Results
An Overview of the Reporting System and Future Plans
Some Findings
Discussion
Summary
Examples of Risk Scoring with Access Queries
The Audit Selection Method of the IRS
Risk Scoring to Detect Banking Fraud
Final Risk Scores
Risk Scoring to Detect Travel Agent Fraud
Final Results
Risk Scoring to Detect Vendor Fraud
Vendor Risk Scoring Using Access
Summary
The Detection of Financial Statement Fraud
The Digits of Financial Statement Numbers
Detecting Biases in Accounting Numbers
An Analysis of Enron's Reported Numbers
An Analysis of Biased Reimbursement Numbers
Detecting Manipulations in Monthly Subsidiary Reports
Predictor Weightings
Conclusions
Summary
Using Analytics on Purchasing Card Transactions
Purchasing Cards
The National Association of Purchasing Card Professionals
A Forensic Analytics Dashboard
An Example of Purchasing Card Data
High-Level Data Overview
The First-Order Test
The Summation Test
The Last-Two Digits Test
The Second-Order Test
The Number Duplication Test
The Largest Subsets Test
The Same-Same-Same Test
The Same-Same-Different Test
The Relative Size Factor Test
Conclusions with Respect to Card Purchases
A Note on Microsoft Office
A Note on the Forensic Analytic Tests
Conclusion
References
Index

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